# Trimmed Mean Calculator Calculate a trimmed mean by removing the same percentage of low and high values before averaging > Canonical page: https://elysiatools.com/en/tools/trimmed-mean-calculator - **Category:** Math & Numbers - **Keywords:** trimmed mean, truncated mean, statistics, outliers, robust average ## Overview Calculate a trimmed mean for a numeric dataset. A trimmed mean sorts the dataset, removes the same percentage of values from the low and high ends, then averages the remaining values. Use it when outliers should be excluded rather than capped, such as survey scores, judging panels, quality metrics, and noisy measurements. ## Inputs - **Dataset** (textarea): e.g. 10, 12, 14, 16, 18, 100 - **Trim Percent Per Tail** (number) - **Decimal Places** (number) - **Include Trimmed Values** (checkbox) ## When to use - When analyzing survey scores or judging panel results where extreme bias might exist. - When processing noisy sensor data or quality metrics that occasionally produce false spikes. - When you need a robust statistical average that completely excludes outliers rather than just capping them. ## How it works - Enter your numeric dataset as a comma-separated list in the input field. - Specify the percentage of values to trim from each tail (e.g., 10% from the top and 10% from the bottom). - The tool sorts the numbers, removes the specified outliers, and calculates the mean of the remaining values. ## Use cases - Calculating final scores in competitive judging by dropping the highest and lowest judge scores. - Evaluating average employee salaries or real estate prices without the distortion of extreme high or low figures. - Filtering out temporary sensor malfunctions when calculating average daily temperatures or machine performance metrics. ## Frequently asked questions ### What is a trimmed mean? A trimmed mean is a method of averaging that removes a small, specified percentage of the largest and smallest values before calculating the mean, reducing the impact of outliers. ### How is the trim percentage applied? The percentage applies to each tail. For example, a 10% trim on a dataset of 100 items will remove the 10 lowest and 10 highest values. ### What is the maximum trim percentage allowed? You can trim up to 45% from each tail. Trimming 50% from both ends would leave no data to average. ### Can I see which values were removed? Yes, by enabling the 'Include Trimmed Values' option, the output will display the specific numbers that were excluded from the final calculation. ### How does this differ from Winsorizing? A trimmed mean completely removes the extreme values from the dataset, whereas Winsorizing replaces those extreme values with the nearest remaining values before averaging. ## Related tools - [Remove Duplicate Lines](https://elysiatools.com/en/tools/remove-duplicate-lines): Deduplicate lines in a list or text block. 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